Data networks are growing in size and complexity. A prime example is the public Internet, which has millions of nodes connected to it across the world. Enterprise networks can also be very large and complex. For example, corporate networks sometimes connect thousands of nodes, and carry multiple types of network traffic, such as IP traffic, Novell IPX traffic, or IBM SNA traffic.
With the complexity and size of data networks, as well as the number of network protocols in use, it can be hard to find or identify a specific entity on a network. Through the use of dynamic addressing protocols such as DHCP and network address translation implementations, an individual may log on to the same network and be given a different network address at each log-in, whether or not the individual is mobile. Effectively, an individual may remain anonymous to network administrators or others that may be trying to locate them. With DHCP, IP addresses are dynamically assigned so that networks can utilize a smaller range of IP addresses. For example, most broadband providers only issue 3-day DHCP leases to their customers, which means that after 3 days a new customer and it's computer might utilize the same IP address, only having those IP addresses tied up which are actually in use on the network.
Even if an individual computer has a static IP address from a particular Internet service provider on the Internet, when that individual changes its Internet service provider, the computer is typically assigned a new IP address, and the computer may enter the network in a completely different location or from a new address space. Another complication is that multiple individuals may use the same machine, such as at a University computer lab or at an Internet Café.
Thus, a network address associated with a single machine may not identify a specific individual, especially in the context of the public Internet. There is a need for another way to identify individuals, other than by a specific network address, like an IP address, or MAC address.
In the context of a telephone network, a similar problem has been addressed by using communities of interest (COIs) to track the specific telephone communications of an individual and to identify a specific individual. In the telecommunications industry, there are many types of fraudulent behavior that have made it beneficial to be able to track and identify fraudulent actors. For example, telephone companies have been able to identify individuals signing up for telephone service with stolen credit cards. By comparing the communication pattern of a previously caught fraudulent actor to a current suspected fraudulent actor, it is easier to make a determination that the person with the same or a similar communication pattern is using a stolen credit card as well. The same example applies to individuals that are not paying their bills for telephone service. If a person's telephone service is cancelled due to delinquent bill payment, and the person then registers for telephone service under a new or false name, it is very likely that the individual's calling pattern would remain the same, and make the person easily identifiable.
The known method of using COIs to track individuals in a telephone network, however, is not readily transferable to a data network. First, telephone networks and data networks typically have distinct underlying technological approaches: a telephone network is usually a circuit switched network, while a data network is usually a packet switched network. In addition, the amount and type of data that is available in a telephone network is related to one application and thus very limited and relatively easy for a telephone service provider to collect. A data network, on the other hand, is much more complex and typically carries multiple types of applications, making information inherently more difficult to track. It can be even more difficult to make use of data gathered from a data network because there is a large amount of additional unusable data exchanged in a single network transaction that does not necessarily represent communication.
Thus, there is a need for a system and method of tracking individuals or identifying entities on a data network such as the Internet.